Hybrid pseudo-random number generator for cryptographic systems

For a powerful cryptographic system, high-quality random number streams are essential. Those raw pseudo-random number generators (PRNG) that are used to generate high-quality random numbers have some disadvantages, such as failure to meet the R4 security requirement. Therefore, use of random number sequences generated by these generators in a cryptographic system puts the entire system at risk. This study proposes a new hybrid PRNG by means of an additional input introduced to transition and output functions used in a raw PRNG system in order to eliminate this risk. The additional inputs to the designed system have been implemented via the true random number generator developed by using the Sprott 94 G chaotic system on FPGA. The random number streams obtained from the recommended hybrid structure have been subjected to the NIST 800.22 and FIPS statistical test, which have given good results. According to these results, it has been proved that the recommended hybrid PRNG system meets the R4 security requirement and can be used in cryptographic applications.

[1]  Kwok-Wo Wong,et al.  A true random number generator based on mouse movement and chaotic cryptography , 2009 .

[2]  Johan A. K. Suykens,et al.  True random bit generation from a double-scroll attractor , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[3]  Çetin Kaya Koç,et al.  About Cryptographic Engineering , 2008, Cryptographic Engineering.

[4]  R. Rovatti,et al.  Embeddable ADC-based true random number generator for cryptographic applications exploiting nonlinear signal processing and chaos , 2005 .

[5]  Xing-yuan Wang,et al.  A new pseudo-random number generator based on CML and chaotic iteration , 2012 .

[6]  P. L’Ecuyer Random Number Generation , 2012 .

[7]  Keith Mayes,et al.  Pseudorandom Number Generation in Smart Cards: An Implementation, Performance and Randomness Analysis , 2012, 2012 5th International Conference on New Technologies, Mobility and Security (NTMS).

[8]  Vincent Rijmen,et al.  The Design of Rijndael: AES - The Advanced Encryption Standard , 2002 .

[9]  Fatih Özkaynak,et al.  Cryptographically secure random number generator with chaotic additional input , 2014 .

[10]  R. Rovatti,et al.  A Fast Chaos-based True Random Number Generator for Cryptographic Applications , 2006, 2006 Proceedings of the 32nd European Solid-State Circuits Conference.

[11]  Andrey Bogdanov,et al.  Biclique Cryptanalysis of the Full AES , 2011, ASIACRYPT.

[12]  James D. Meindl,et al.  Solid-State Circuits Conference , 1969 .

[13]  Dan Boneh,et al.  Ensuring high-quality randomness in cryptographic key generation , 2013, CCS.

[14]  Vincent Rijmen,et al.  The Design of Rijndael , 2002, Information Security and Cryptography.

[15]  Young-Sik Kim,et al.  Fast Digital TRNG Based on Metastable Ring Oscillator , 2008, CHES.

[16]  Ahmad Beirami,et al.  A performance metric for discrete-time chaos-based truly random number generators , 2008, 2008 51st Midwest Symposium on Circuits and Systems.

[17]  Ihsan Pehlivan,et al.  Implementation of FPGA-based real time novel chaotic oscillator , 2014 .

[18]  Knut Wold Security Properties of a Class of True Random Number Generators in Programmable Logic , 2011 .